NDLI: Traffic variable estimation and traffic signal control based on soft computation

Content Provider	IEEE Xplore Digital Library
Author	Lu Conglin Wei Wu Tan Yuejin
Copyright Year	2004
Description	Author affiliation: Sch. of Humanity & Manage., Nat. Univ. of Defense Technol., Changsha, China (Lu Conglin)
Abstract	This paper studies traffic variable estimation, and presents a method of estimation for the number of vehicle waiting for queue (NVWQ) based on neuro-fuzzy at urban intersection. We present results of training the neural network for a detectorized intersection in Changsha City. The accuracy of NVWQ estimation using the fuzzy neural networks approaches is more than 90%. The fuzzy neural networks have the advantages of both fuzzy expert systems (knowledge representation) and artificial neural networks (learning). The fuzzy neural networks can be trained successfully to estimate NVWQ for different traffic flow patterns and different conditions of intersection. This greatly reduces a lot of effort of extracting a traffic expert's knowledge into fuzzy if-then rules. All we have to do is to present the training data to the network which can figure out its own rules through internal representation. In the traffic signal control system, detection of traffic variables at intersection, such as NVWQ is very important and is the basic input data to determine signal timing. We also discuss traffic signal control based on fuzzy system and genetic algorithms (GA). The fuzzy controller has the ability to adjust its signal timing in response to the changing traffic conditions on a real-time basis. Our proposed controller produces lower vehicle delays and percentage of stopped vehicles than the traffic-actuated controller.
Starting Page	1045
Ending Page	1050
File Size	439647
Page Count	6
File Format	PDF
ISBN	0780385004
DOI	10.1109/ITSC.2004.1399051
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-10-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Traffic control Communication system traffic control Fuzzy control Vehicles Fuzzy neural networks Artificial neural networks Control systems Timing Cities and towns Hybrid intelligent systems
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A method of traffic variable estimation based on neuro-fuzzy on urban road

Intelligent traffic signal system based on networked control

An Intelligent Control Method for Urban Traffic Signal Based on Fuzzy Neural Network

Research on traffic signal control based on intelligence techniques

A neural network application in signal timing control

Research on Signal Control Methods of Traffic Bottlenecks in City Road Network

A road tunnel longitudinal ventilation control system based on fuzzy-neural network

Fuzzy Rule Based Traffic Signal Control System for Oversaturated Intersections

Traffic Signal control optimization based on fuzzy neural network

Traffic variable estimation and traffic signal control based on soft computation

Similar Documents

A method of traffic variable estimation based on neuro-fuzzy on urban road

Intelligent traffic signal system based on networked control

An Intelligent Control Method for Urban Traffic Signal Based on Fuzzy Neural Network

Research on traffic signal control based on intelligence techniques

A neural network application in signal timing control

Research on Signal Control Methods of Traffic Bottlenecks in City Road Network

A road tunnel longitudinal ventilation control system based on fuzzy-neural network

Fuzzy Rule Based Traffic Signal Control System for Oversaturated Intersections

Traffic Signal control optimization based on fuzzy neural network

Traffic variable estimation and traffic signal control based on soft computation